“AI”, “machine learning”, “big data”, “1:1 personalization”, “omni-channel marketing”, “right message at the right time to the right device”—rolling your eyes already as you read these terms? You are not alone. Everyday it appears we are at the peak of the buzzword phase, only to see things getting more and more foggy for cloud computing (pun intended).
In all seriousness, the overuse of buzzwords creates 3 issues:
- There are way too many companies, especially in the marketing tech ecosystem, that say similar things about what they do, which makes it hard to assess who does what well. Go ahead and give it a try—do a Google search for “marketing AI” and try and figure out the difference between the more than 8 million results.
- Then there is the issue of the overuse of buzzwords to the extent where one has no idea what the company does. Take this, for instance: “The world’s leading AI and IoT software platform for digital transformation, <redacted company name> delivers a comprehensive platform as a service (PaaS) for rapidly developing and operating big data, predictive analytics, AI/machine learning, and IoT software as a service (SaaS) applications.” Are there any more buzzwords left to optimize for SEO? What does the product do, though? One can only guess…
- And finally, in the zeal to join the buzzword bandwagon, companies use terms that are deceptive at best, when it comes to representing their real, actual product—not what they would like it to be. For example: there are websites talking about “AI powered 1:1 experiences”—does the product really have customer journeys tailored to the individual, or is it simply adding personalized content and personalized product recommendations to the email?
Taking the first step to address these issues
It is with this background, we at Kahuna decided we need to do something about it. Lead by example and make it very clear through our messaging—what is it that we actually do?
Kahuna makes your consumer messaging intelligent. We help you answer your hardest marketing questions—questions related to engaging and messaging your consumers, such as: Who should you target? Where in their customer journey should you message them? Will messaging help or hurt? Which channel or device should I send the message on? Do I know if the person I sent an email to will receive a duplicate message if I send them an SMS? And so on. In doing so, we reduce guesswork and help you make better decisions, enabling you to get back to what you do best—marketing.
Kahuna is able to answer these tough questions because:
- Kahuna’s product is built to understand the consumer across multiple channels. We collect billions of real-time consumer events in seconds that inform us about consumer preferences and behaviors, and we leverage that data to build individual consumer profiles for each consumer.
- Based on these profiles, we apply machine learning models to make inferences at the individual level. For instance, to determine the right channel an individual prefers receiving a message on, we built what’s called a “Non-Annealing Boltzmann Based Multi Armed Bandit” model to figure this out.
- And finally, to act on these decisions, we offer campaigns and customer journey features (what we call Experiences) which deliver messages to the consumers—messages delivered either by us or by integrating with customers’ existing martech stacks.
Sifting the real stuff from the noise
We get it; even now, this may sound similar to what you may have heard before. To help you understand why we are excited about our product, we have put together the following questions to help you reflect and assess your current or future consumer messaging platform. Ask yourself or your prospective vendor if they can do the following for you (we can):
Cross-channel: The term “cross-channel” gets thrown out a lot and most often. It refers to how messages can be delivered via email, push notifications, SMS, social, etc. But what is also important is to act on cross-channel signals. For instance, can the product send either an email, an SMS, or a push notification in real time as it gathers signals from your website? Say a visitor browses for shoes on your website but does not buy. The product needs to “listen” to the signals on the website and decide at an individual level which channel they get messaged on.
Customer experience: The term “customer experience” gets thrown out a lot and while the intent is noble (making sure the consumer gets a consistent experience when it comes to interactions with your brand), does the product indeed help you get there? For instance, does your product know that if you sent a consumer an email yesterday with a “buy one, get one free” offer, you shouldn’t send them a push notification today for a full-priced offer for the same product?
Cart abandonment: The term “cart abandonment” gets thrown out a lot. Here, emails are sent to people who have not completed the checkout process after adding items to their digital shopping cart. Does the product know, however, when to send the email and who to send it to? The timing can be tricky. Sending a message too soon risks annoying users who would complete purchases organically, yet sending the message too late misses the window of opportunity. Does the product figure out how long to wait before messaging, to maximize conversions?
Learn more at Kahuna’s refreshed website
There are many more examples such as these. Kahuna’s intent is to do our part to reduce the noise in the market by providing clarity about what we do. To that end, we are pleased to announce a revamp of our website which reflects this clarity and focus. It has many more examples of the types of manners in which we make consumer messaging intelligent. Check it out by clicking the button below—and let us know what you think!